Analyzing the Effect of Fluorescence Characteristics on Leaf Nitrogen Concentration Estimation

Leaf nitrogen concentration (LNC) is a significant indicator of crops growth status, which is related to crop yield and photosynthetic efficiency. Laser-induced fluorescence is a promising technology for LNC estimation and has been widely used in remote sensing. The accuracy of LNC monitoring relies greatly on the selection of fluorescence characteristics and the number of fluorescence characteristics. It would be useful to analyze the performance of fluorescence intensity and ratio characteristics at different wavelengths for LNC estimation. In this study, the fluorescence spectra of paddy rice excited by different excitation light wavelengths (355 nm, 460 nm, and 556 nm) were acquired. The performance of the fluorescence intensity and fluorescence ratio of each band were analyzed in detail based on back-propagation neural network (BPNN) for LNC estimation. At 355 nm and 460 nm excitation wavelengths, the fluorescence characteristics related to LNC were mainly located in the far-red region, and at 556 nm excitation wavelength, the red region being an optimal band. Additionally, the effect of the number of fluorescence characteristics on the accuracy of LNC estimation was analyzed by using principal component analysis combined with BPNN. Results demonstrate that at least two fluorescence spectral features should be selected in the red and far-red regions to estimate LNC and efficiently improve the accuracy of LNC estimation.

[1]  M. Brestič,et al.  Application of chlorophyll fluorescence performance indices to assess the wheat photosynthetic functions influenced by nitrogen deficiency. , 2018 .

[2]  W. Gong,et al.  Effect of fluorescence characteristics and different algorithms on the estimation of leaf nitrogen content based on laser-induced fluorescence lidar in paddy rice. , 2017, Optics express.

[3]  Filippo Bussotti,et al.  Frequently asked questions about chlorophyll fluorescence, the sequel , 2016, Photosynthesis Research.

[4]  Wei Gong,et al.  Analyzing the performance of fluorescence parameters in the monitoring of leaf nitrogen content of paddy rice , 2016, Scientific Reports.

[5]  Wei Gong,et al.  Accurate identification of nitrogen fertilizer application of paddy rice using laser-induced fluorescence combined with support vector machine , 2016 .

[6]  Marek Zivcak,et al.  Chlorophyll a fluorescence as a tool to monitor physiological status of plants under abiotic stress conditions , 2016, Acta Physiologiae Plantarum.

[7]  Li He,et al.  Improved remote sensing of leaf nitrogen concentration in winter wheat using multi-angular hyperspectral data , 2016 .

[8]  Andrei B. Utkin,et al.  The use of laser induced chlorophyll fluorescence (LIF) as a fast and non‑destructive method to investigate water deficit in Arabidopsis , 2016 .

[9]  U. Rascher,et al.  Plant chlorophyll fluorescence: active and passive measurements at canopy and leaf scales with different nitrogen treatments , 2015, Journal of experimental botany.

[10]  Aiwang Duan,et al.  Rapid and nondestructive estimation of the nitrogen nutrition index in winter barley using chlorophyll measurements , 2016 .

[11]  M. Zivcak,et al.  Effect of photosystem I inactivation on chlorophyll a fluorescence induction in wheat leaves: Does activity of photosystem I play any role in OJIP rise? , 2015, Journal of photochemistry and photobiology. B, Biology.

[12]  Peng Xu,et al.  Monitoring the chlorophyll fluorescence parameters in rice under flooding and waterlogging stress based on remote sensing , 2014, 2014 World Automation Congress (WAC).

[13]  Magdalena D. Cetner,et al.  Identification of nutrient deficiency in maize and tomato plants by in vivo chlorophyll a fluorescence measurements. , 2014, Plant physiology and biochemistry : PPB.

[14]  Age K. Smilde,et al.  Principal Component Analysis , 2003, Encyclopedia of Machine Learning.

[15]  Vladimir Alexandrov,et al.  Artificial neural networks and their application in biological and agricultural research , 2014 .

[16]  Fei Li,et al.  Reflectance estimation of canopy nitrogen content in winter wheat using optimised hyperspectral spectral indices and partial least squares regression , 2014 .

[17]  Francesco Montemurro,et al.  Precision nitrogen management of wheat. A review , 2012, Agronomy for Sustainable Development.

[18]  Nicolas Tremblay,et al.  Sensing crop nitrogen status with fluorescence indicators. A review , 2011, Agronomy for Sustainable Development.

[19]  Xin Huang,et al.  Wavelength selection and spectral discrimination for paddy rice, with laboratory measurements of hyperspectral leaf reflectance , 2011 .

[20]  X. Yao,et al.  Assessing newly developed and published vegetation indices for estimating rice leaf nitrogen concentration with ground- and space-based hyperspectral reflectance , 2011 .

[21]  Denis Klimov,et al.  Monitoring of cold and light stress impact on photosynthesis by using the laser induced fluorescence transient (LIFT) approach , 2010 .

[22]  Luis Alonso,et al.  Remote sensing of solar-induced chlorophyll fluorescence: Review of methods and applications , 2009 .

[23]  Z. Malenovský,et al.  Scientific and technical challenges in remote sensing of plant canopy reflectance and fluorescence. , 2009, Journal of experimental botany.

[24]  M. Boschetti,et al.  Plant nitrogen concentration in paddy rice from field canopy hyperspectral radiometry , 2009 .

[25]  E. Middleton,et al.  Contribution of chlorophyll fluorescence to the apparent vegetation reflectance. , 2008, The Science of the total environment.

[26]  Xia Yao,et al.  Monitoring leaf nitrogen status with hyperspectral reflectance in wheat , 2008 .

[27]  Fumin Wang,et al.  Monitoring rice nitrogen status using hyperspectral reflectance and artificial neural network. , 2007, Environmental science & technology.

[28]  Nicolas Tremblay,et al.  A comparison of multiwavelength laser-induced fluorescence parameters for the remote sensing of nitrogen stress in field-cultivated corn , 2007 .

[29]  G. Mauromicale,et al.  Chlorophyll fluorescence and chlorophyll content in field-grown potato as affected by nitrogen supply, genotype, and plant age , 2006, Photosynthetica.

[30]  P. Buah-Bassuah,et al.  Using violet laser-induced chlorophyll fluorescence emission spectra for crop yield assessment of cowpea (Vigna unguiculata (L) Walp) varieties , 2004 .

[31]  G. Krause,et al.  Chlorophyll fluorescence as a tool in plant physiology , 1984, Photosynthesis Research.

[32]  S. Ustin,et al.  Water content estimation in vegetation with MODIS reflectance data and model inversion methods , 2003 .

[33]  I. Rademacher,et al.  Estimation of nitrogen deficiency of sugar beet and wheat using parameters of laser induced and pulse amplitude modulated chlorophyll fluorescence , 2003 .

[34]  James S. Schepers,et al.  Detection of Phosphorus and Nitrogen Deficiencies in Corn Using Spectral Radiance Measurements , 2002 .

[35]  M. A. Pizarro,et al.  Variations in Reflectance of Tropical Soils: Spectral-Chemical Composition Relationships from AVIRIS data , 2001 .

[36]  Xiao‐Hai Yan,et al.  A Neural Network Model for Estimating Sea Surface Chlorophyll and Sediments from Thematic Mapper Imagery , 1998 .

[37]  Y Saito,et al.  Investigation of laser-induced fluorescence of several natural leaves for application to lidar vegetation monitoring. , 1998, Applied optics.

[38]  Hartmut K. Lichtenthaler,et al.  Differences in Fluorescence Excitation Spectra of Leaves between Stressed and Non-Stressed Plants , 1996 .

[39]  W. Lüdeker,et al.  Remote sensing vegetation status by laser-induced fluorescence , 1994 .

[40]  Giovanna Cecchi,et al.  Remote sensing of chlorophyll a fluorescence of vegetation canopies: 1. Near and far field measurement techniques , 1994 .

[41]  Narayanan Subhash,et al.  Laser-induced red chlorophyll fluorescence signatures as nutrient stress indicator in Rice Plants , 1994 .

[42]  Moon S. Kim,et al.  Identification of the pigment responsible for the blue fluorescence band in the laser induced fluorescence (LIF) spectra of green plants, and the potential use of this band in remotely estimating rates of photosynthesis , 1991 .

[43]  J. McMurtrey,et al.  Laser-induced fluorescence of green plants. 3: LIF spectral signatures of five major plant types. , 1985, Applied optics.

[44]  R. Swift,et al.  Feasibility of airborne detection of laser-induced fluorescence emissions from green terrestrial plants. , 1983, Applied optics.

[45]  J. Kjeldahl,et al.  Neue Methode zur Bestimmung des Stickstoffs in organischen Körpern , 1883 .